1 code implementation • 1 Mar 2024 • Zenan Li, Zehua Liu, Yuan YAO, Jingwei Xu, Taolue Chen, Xiaoxing Ma, Jian Lü
In this paper, we present a new framework for learning with logical constraints.
1 code implementation • 1 Mar 2024 • Zenan Li, Yuan YAO, Taolue Chen, Jingwei Xu, Chun Cao, Xiaoxing Ma, Jian Lü
Neuro-symbolic learning generally consists of two separated worlds, i. e., neural network training and symbolic constraint solving, whose success hinges on symbol grounding, a fundamental problem in AI.
1 code implementation • 21 Nov 2023 • Yunpeng Huang, Jingwei Xu, Junyu Lai, Zixu Jiang, Taolue Chen, Zenan Li, Yuan YAO, Xiaoxing Ma, Lijuan Yang, Hao Chen, Shupeng Li, Penghao Zhao
Transformer-based Large Language Models (LLMs) have been applied in diverse areas such as knowledge bases, human interfaces, and dynamic agents, and marking a stride towards achieving Artificial General Intelligence (AGI).
1 code implementation • 10 Dec 2022 • Yedi Zhang, Zhe Zhao, Fu Song, Min Zhang, Taolue Chen, Jun Sun
Experimental results on QNNs with different quantization bits confirm the effectiveness and efficiency of our approach, e. g., two orders of magnitude faster and able to solve more verification tasks in the same time limit than the state-of-the-art methods.
no code implementations • 12 Mar 2021 • Yedi Zhang, Zhe Zhao, Guangke Chen, Fu Song, Taolue Chen
Verifying and explaining the behavior of neural networks is becoming increasingly important, especially when they are deployed in safety-critical applications.
1 code implementation • 18 Sep 2020 • Hengjun Zhao, Xia Zeng, Taolue Chen, Zhiming Liu, Jim Woodcock
We provide a novel approach to synthesize controllers for nonlinear continuous dynamical systems with control against safety properties.
no code implementations • 7 Jun 2020 • Raid R. O. Al-Nima, Tingting Han, Taolue Chen, Satnam Dlay, Jonathon Chambers
\begin{abstract} In recent years, the Finger Texture (FT) has attracted considerable attention as a biometric characteristic.
no code implementations • 4 Feb 2020 • Yu Zhou, Xinying Yang, Taolue Chen, Zhiqiu Huang, Xiaoxing Ma, Harald Gall
In this paper, we propose a framework, BRAID (Boosting RecommendAtion with Implicit FeeDback), which leverages learning-to-rank and active learning techniques to boost recommendation performance.
no code implementations • 27 Nov 2018 • Yedi Zhang, Fu Song, Taolue Chen
Alternating-time temporal logics (ATL/ATL*) represent a family of modal logics for reasoning about agents' strategic abilities in multiagent systems (MAS).